Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050
Demographic aging results in a growing number of older people in need of care in many regions all over the world. Germany has witnessed steady population aging for decades, prompting policymakers and other stakeholders to discuss how to fulfill the rapidly growing demand for care workers and finance...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-10-01
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| Series: | Econometrics |
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| Online Access: | https://www.mdpi.com/2225-1146/12/4/28 |
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| author | Patrizio Vanella Christina Benita Wilke Moritz Heß |
| author_facet | Patrizio Vanella Christina Benita Wilke Moritz Heß |
| author_sort | Patrizio Vanella |
| collection | DOAJ |
| description | Demographic aging results in a growing number of older people in need of care in many regions all over the world. Germany has witnessed steady population aging for decades, prompting policymakers and other stakeholders to discuss how to fulfill the rapidly growing demand for care workers and finance the rising costs of long-term care. Informed decisions on this matter to ensure the sustainability of the statutory long-term care insurance system require reliable knowledge of the associated future costs. These need to be simulated based on well-designed forecast models that holistically include the complexity of the forecast problem, namely the demographic transition, epidemiological trends, concrete demand for and supply of specific care services, and the respective costs. Care risks heavily depend on demographics, both in absolute terms and according to severity. The number of persons in need of care, disaggregated by severity of disability, in turn, is the main driver of the remuneration that is paid by long-term care insurance. Therefore, detailed forecasts of the population and care rates are important ingredients for forecasts of long-term care insurance expenditures. We present a novel approach based on a stochastic demographic cohort-component approach that includes trends in age- and sex-specific care rates and the demand for specific care services, given changing preferences over the life course. The model is executed for Germany until the year 2050 as a case study. |
| format | Article |
| id | doaj-art-31437a9912914ed3a92e4a8dbbd8ab45 |
| institution | DOAJ |
| issn | 2225-1146 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Econometrics |
| spelling | doaj-art-31437a9912914ed3a92e4a8dbbd8ab452025-08-20T02:53:34ZengMDPI AGEconometrics2225-11462024-10-011242810.3390/econometrics12040028Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050Patrizio Vanella0Christina Benita Wilke1Moritz Heß2Demography Cluster, Department of Health Monitoring & Biometrics, aQua Institute, 37073 Göttingen, GermanyChair of Economics, FOM University of Applied Sciences, 28359 Bremen, GermanyKompetenzzentrum Ressourcenorientierte Alter(n)sforschung, Hochschule Niederrhein, 41065 Mönchengladbach, GermanyDemographic aging results in a growing number of older people in need of care in many regions all over the world. Germany has witnessed steady population aging for decades, prompting policymakers and other stakeholders to discuss how to fulfill the rapidly growing demand for care workers and finance the rising costs of long-term care. Informed decisions on this matter to ensure the sustainability of the statutory long-term care insurance system require reliable knowledge of the associated future costs. These need to be simulated based on well-designed forecast models that holistically include the complexity of the forecast problem, namely the demographic transition, epidemiological trends, concrete demand for and supply of specific care services, and the respective costs. Care risks heavily depend on demographics, both in absolute terms and according to severity. The number of persons in need of care, disaggregated by severity of disability, in turn, is the main driver of the remuneration that is paid by long-term care insurance. Therefore, detailed forecasts of the population and care rates are important ingredients for forecasts of long-term care insurance expenditures. We present a novel approach based on a stochastic demographic cohort-component approach that includes trends in age- and sex-specific care rates and the demand for specific care services, given changing preferences over the life course. The model is executed for Germany until the year 2050 as a case study.https://www.mdpi.com/2225-1146/12/4/28long-term care insurancepublic financedemographyeconometricsforecastingtime-series analysis |
| spellingShingle | Patrizio Vanella Christina Benita Wilke Moritz Heß Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050 Econometrics long-term care insurance public finance demography econometrics forecasting time-series analysis |
| title | Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050 |
| title_full | Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050 |
| title_fullStr | Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050 |
| title_full_unstemmed | Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050 |
| title_short | Long-Term Care in Germany in the Context of the Demographic Transition—An Outlook for the Expenses of Long-Term Care Insurance through 2050 |
| title_sort | long term care in germany in the context of the demographic transition an outlook for the expenses of long term care insurance through 2050 |
| topic | long-term care insurance public finance demography econometrics forecasting time-series analysis |
| url | https://www.mdpi.com/2225-1146/12/4/28 |
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